可調式視訊編碼是以階層式雙向B畫面編碼為主要結構，為的是達成時間域的可調性以及更佳的編碼效率。一般而言，在每一個畫面群組中，畫面的內容變動能敘述畫面群組中的畫面在時間域中的變化狀態。因此，要如何決定視訊中的畫面群組大小是一個重要的問題。本論文將提出依照畫面內容複雜程度適應性選擇畫面群組的演算法，以階層式雙向B畫面預測的方式計算畫面之間的差異值，並且利用其資訊作為畫面群組大小決策的基準，如此一來我們可以得到一組合適的畫面群組。實驗數據中的位元率失真曲線顯示所提出的演算法與可調式視訊編碼內之階層式B畫面編碼比較之結果。

The hierarchical B picture coding is introduced into the extension of H.264/AVC in order to improve coding performance and provide temporal scalability as well. In general, coding performance is affected by the content variation in each GOP (Group of Picture). Therefore, the ways to determine the size of sun-GOP is a critical problem for video coding. In this thesis, the adaptive GOP structure determination scheme is proposed to select the appropriate sub-GOP size with content complexity consideration. We compute the frame difference by hierarchical B picture structure and use the information to be a basis of sub-GOP decision. Hence, we can get proper combination of sub-GOP. Experimental results show the RD curves that our proposed method compares with the fixed GOP setting in the existing hierarchical B picture coding of SVC.

CHAPTER 1 Introduction…………………………………………………1
1.1 Overview of Video Coding………………………………………………1
1.2 Overview of H.264/AVC Video Coding Standard………………………4
1.3 Motivation………………………………………………………………7
1.4 The Organization of the Thesis…………………………………………9
CHAPTER 2 Overview of Scalable Video Coding and Relevant Work…………10
2.1 Overview of Scalable Video Coding………………………………10
2.1.1 Spatial Scalability………………………………………………12
2.1.2 Temporal Scalability……………………………………………13
2.1.2 Quality Scalability…………………………………………………14
2.2 Inter-layer Prediction……………………………………………………16
2.2.1 Inter-Layer Motion Prediction…………………………………16
2.2.2 Inter-Layer Intra Prediction…………………………………18
2.2.3 Inter-Layer Residual Prediction…………19
2.3 Hierarchical B Picture…………………………………………………20
2.4 Relevant Works of adaptive GOP Structure Coding…………………22
2.4.1 Adaptive GOP Structure for SVC……………………………………22
2.4.2 Fast Prediction Algorithm of Adaptive GOP Structure for SVC……23
2.4.3 Fast Adaptive GOP Design for H.264/SVC…………………………25
2.4.4 Visual Rhythm………………………………………………………27
CHAPTER 3 Proposed Adaptive GOP Structure Coding……………32
3.1 Measurement of Video Variation by Frame Difference of Hierarchical
Structure …………………………………………………………………32
3.2 AGS Determination……………38
CHAPTER 4 Experimental Results………………………40
4.1 Testing Platform of Experimental Results………………40
4.2 Performance comparison…………………………………42
CHAPTER 5 Conclusions and Future Work……………………………………45
5.1 Conclusions……………………………………………………………45
5.2 Future Work………………………………………………………………46
Bibliography…………………………………………………………………………47

[1] K.-N. Nign, C.-W. Yap and K.-T. Tan, Video coding for wireless communication. New Jersey: Prentice Hall, 2002.
[2] A.-M. Tekalp, Digital Video Processing. New Jersey: Prentice Hall PTR, 1995.
[3] Y. Wang, J. Ostermann and Y.-Q. Zhang, Video Processing and Communications. New Jersey: Prentice Hall, 2002.
[4] M.-T. Sun and A.-R. Reibman, Compressed Video over Networks. New Work: Marcel Dekker, 2001.
[5] Video codec for audiovisual services at p×64 kbit/s, CCITT Recommendation H.261, 1990.
[6] CCITT SGXV, “Description of reference model 8 (RM8),” Document 525, Working Party XV/4, Specialists Group on Coding for Visual Telephony, 1989.
[7] ITU Telecommunication Standardization Sector LBC-95, Study Group 15, Working Party 15/1, Expert’s Group on Very Low Bitrate Visual Telephony, available from Digital Video Coding Group, Telenor Research and Development; or via http://www.nta.no/brukere/DVC/tmn5, 1998.
[8] H. Yu, F. Pan and Z. Lin, “Content adaptive rate control for H.264,” Int. J. of Innovative Computing, Information and Control, vol. 1, no. 4, pp. 685-700, 2005.
[9 ] ISO/IEC CD 11172-2 (MPEG-1 Video), “Information technology－coding of moving pictures and associated audio for digital storage media at up to about 1.5 Mbits,” video, 1993.
[10] ISO/IEC CD 13818-2-ITU-T H.262 (MPEG-2 Video), “Information technology－generic coding of moving pictures and associated audio information,” video, 1995.
[11] ITU-T Recommendation H.264 & ISO/IEC 14496-10 (MPEG-4) AVC. Advance video coding for generic audiovisual services. (version 1: 2003, version 2: 2004, version 3 : 2005).
[12] K. De Wolf, D. De Schrijver, S. De Zutter and R. Van de Walle, “Scalable video coding: analysis and coding performance of inter-layer prediction,” in Proceedings of IEEE International Symposium on Signal Processing and Its Application (ISSPA), pp. 1-4, 2007.
[13] E. Akyvol, A, Tekulp, and M. Civanlur, “Motion-compensated temporal filtering within the H.264/AVC standard,” in proceedings of International Conference on Image Processing (ICIP), vol. 4, pp. 2291-2294, October 2004.
[14] G. H. Park, M. W. Park, S. Jeong, K. K. Kim, and J. Hong, “Improve SVC coding efficiency by adaptive GOP structure,”Joint Video Team, Doc. JVT-O018, Busan, Korea, April 2005.
[15] M. W. Park, G. H. Park, S. Jeong, D. Y. Suh, and K. Kim, “Adaptive GOP structure for joint scalable video coding,” IEICE Transactions on Communications, vol. E90-B, no. 2, pp. 431-434, February 2007.
[16] J. Reichel, H. Schward and M. Wien, Joint Scalable Video Model (JSVM) 1.0 Reference Encoding Algorithm Description, ISO/IEC JTC 1/SC 29/WG 11 N6899, Hong Kong, China, January 2005.
[17] Y. H. Chen, C. H. Lin, C. Y. Chen, and L. G. Chen, “Fast prediction algorithm of adaptive GOP structure of SVC,” in Proceedings of SPIE Visual Communications and Image Processing, vol. 6508, January 2007.
[18] J. R. Ding, J. F. Yang, “Fast adaptive GOP design for H.264/SVC,” in Proceedings of IEEE Region 10 Conference (TENCON), pp. 1-4, November 2007.
[19] L. Cao and C. W. Chen, “Content-based multiple bit stream image transmission over noisy channels,” IEEE Transactions on Image Processing, vol. 11, no. 11, pp. 1305-1313, November 2002.
[20] R. L. Joshi, H. Jafarkhani, J. H. Kasner, T. R. Fischer, N. Farvardin, M. W. Marcellin and R. H. Bamberger, “Comparison of different methods of classification in subband coding of images,” IEEE Transactions on Image Processing, vol. 6, no. 11, pp. 1473-1485, November 1997.
[21] M. G. Chung, J Lee, H Kim, S. M. H. Song, and W. M. Kim, “Automatic video segmentation based on spatio-temporal features,” Korea Telcom Journal, vol. 1, no. 4, pp. 4-14, 1999.
[22] H. Kim, J. Lee and S. Moon-Ho Song, “An efficient graphical shot verifier incorporating visual rhythm,” in Proceedings of IEEE International Conference on Multimedia Computing and Systems, vol. 1, pp. 827-834, June 1999.
[23] S. Jamil F. Giuimaraes, M. Couprie, N. J. Leite, and A. De A. Araujo, “A method for cut detection based on visual rhythm,” in Proceedings of XIV Brazilian Symposium on Computer Graphics and Image Processing, pp. 297-304, October 2001.